METHOD, APPARATUS AND SYSTEM FOR MULTIMEDIA MODEL RETRIEVAL

• US 20090070329A1
• Filed: 09/05/2008
• Published: 03/12/2009
• Est. Priority Date: 09/06/2007
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Inventors: ZHANG, Qinwei, MA, Yanping
• Granted Patent: US 8,082,263 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/434 using image data, e.g. images, photos, pictures taken by a user
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

A method, apparatus and system for multimedia model retrieval are provided. The method includes: obtaining parameters of a multimedia model to be retrieved; performing a projection on the multimedia model according to the parameters of the multimedia model so as to obtain a projection image; performing a feature extraction on the projection image; matching a feature extraction result with stored model multimedia file information to obtain a retrieval result; training a support vector machine (SVM) with the multimedia model labeled by a user upon the retrieval result as a training sample set, performing a probability-based classification on the multimedia model by the SVM, and updating the retrieval result with a classification result. The system of the present invention illustrated by embodiments achieves favorable applicability and robustness, so that users may perform a rapid and precise retrieval on massive model data in these fields.

Claims

1. A method for multimedia model retrieval, comprising:

acquiring parameters of a multimedia model to be retrieved;

performing a projection on the multimedia model according to the parameters of the multimedia model so as to obtain a projection image;

performing a feature extraction on the projection image;

matching a feature extraction result with stored model multimedia file information so as to obtain a retrieval result; and

training a support vector machine with the multimedia model labeled by a user upon the retrieval result as a training sample set, performing a probability-based classification on the multimedia model by the support vector machine and updating the retrieval result with a classification result.

2. The method according to claim 1, wherein the performing the feature extraction on the projection image comprises:

performing the feature extraction on the multimedia model by using a Zernike moment.

3. The method according to claim 1, further comprising:

performing a pre-processing on the acquired parameters of the multimedia model to be retrieved.

4. The method according to claim 2, further comprising:

performing a pre-processing on the acquired parameters of the multimedia model to be retrieved.

5. The method according to claim 3, wherein the pre-processing comprises:

performing an isotropic transformation on the acquired multimedia model; and

performing a vertex sampling according to the multimedia model after the isotropic transformation.

6. The method according to claim 1, wherein the training the support vector machine with the multimedia model labeled by the user upon the retrieval result as a training sample set and the performing the probability-based classification on the multimedia model by the support vector machine specifically comprises:

employing a user manual label as a training sample and training according to the training sample to obtain the support vector machine; and

forecasting models in a database by using the support vector machine.

7. The method according to claim 6, wherein the user manual label is that a weight of a relevant model is 1 and the weight of an irrelevant model is −

1.

8. The method according to claim 6, wherein the forecasting models in the database by using the support vector machine comprises:

forecasting each of the models in the database, obtaining relevant or irrelevant probability values attributed to each of the models and revising a similarity degree by the probability values.

9. The method according to claim 1, wherein the performing the projection on the multimedia model according to the parameters of the multimedia model comprises:

performing a spherical projection on a three-dimensional multimedia model and calculating a spherical projection image.

10. The method according to claim 1, further comprising:

sorting the retrieval result obtained by matching or the updated retrieval result.

11. The method according to claim 1, wherein a file format of the acquired parameters of the multimedia model to be retrieved is a three-dimensional model file format 0.3ds or a text file format.txt.

12. The method according to claim 1, wherein the probability-based classification comprises a classification which is based on posterior probability and classified to similarity.

13. An apparatus for multimedia model retrieval, comprising:

a model file initializing module adapted to acquire parameters of a multimedia model to be retrieved;

a projecting module adapted to perform a projection on the multimedia model according to the parameters of the multimedia model so as to obtain a projection image;

a feature extracting module adapted to perform a feature extraction on the projection image;

a similarity degree matching module adapted to match a feature extraction result with stored model multimedia file information so as to obtain a retrieval result; and

a feedback module adapted to train a support vector machine with the multimedia model labeled by a user upon the retrieval result as a training sample set, perform a probability-based classification on the multimedia model by the support vector machine and update the retrieval result with a classification result.

14. The apparatus according to claim 13, further comprising:

a pre-processing module adapted to perform a pre-processing on the acquired parameters of the multimedia model to be retrieved.

15. The apparatus according to claim 14, wherein the pre-processing module further comprises:

an isotropic transforming unit adapted to perform an isotropic transformation on the acquired multimedia model; and

a vertex sampling unit adapted to perform a vertex sampling on the multimedia model after the isotropic transformation.

16. The apparatus according to claim 13, wherein the feedback module comprises:

a support vector machine training unit adapted to employ a user manual label as a training sample and train according to the training sample to obtain the support vector machine; and

a support vector machine forecasting unit adapted to forecast models in a database by using the support vector machine.

17. The apparatus according to claim 13, further comprising:

a similarity degree sorting module adapted to sort the retrieval result obtained by matching or the updated retrieval result.

18. A system for multimedia model retrieval, comprising:

a database management system adapted to store multimedia model file information;

a model retrieval apparatus adapted to acquire parameters of a multimedia model to be retrieved, perform a projection on the multimedia model according to the parameters of the multimedia model so as to obtain a projection image, perform a feature extraction on the projection image, match a feature extraction result with multimedia file information stored in the database management system to obtain a retrieval result, train a support vector machine with the multimedia model labeled by a user upon the retrieval result as a training sample set, perform a probability-based classification on the multimedia model by the support vector machine and update the retrieval result with a classification result.